This proposal aims at developing the candidate's ability to perform multidisciplinary research in Neuroimaging through didactic training in Neuroscience and research in Medical Image Processing at the Johns Hopkins University. The research project consists in creating an automated, quantitative processing framework for structural brain MRI based on the use of topology as a means to introduce global, qualitative anatomical information. It proposes to develop novel brain image segmentation techniques encompassing multi-modality studies, pathologies, and the processing of DTI, to build topological atlases of the human brain, to develop tools for shape analysis and homeomorphic image alignment, and to study structural variations in MDMA (ecstasy) users and Multiple Sclerosis (MS) patients. The segmentation framework will combine recent advances in topology-preserving segmentation, tissue classification, statistical atlases and tensor computing to automatically segment the major structures of the brain, lesions, and white matter fiber bundles. Atlases of brain topology will model structure and connectivity in the brain based on neuroanatomy training, medical atlases and annotated databases. The analysis will combine shape measurements with diffeomorphic registration to provide global and local quantification of structure in two complementary studies: a study of subtle morphometric changes in the brain of users of the drug MDMA, and a longitudinal study of Multiple Sclerosis patients with various levels of lesion and atrophy. The tools will become freely available to neuroscience researchers once fully validated. [unreadable] PUBLIC HEALTH RELEVANCE: The impact of the proposed research in the neuroscience and medical communities will be the release of software to segment and align brain MR images with no manual interaction for a large variety of imaging studies, the modeling of structure and connectivity relationships in brain anatomy from topological properties, and the application to two important questions of neurosciences, the detection and quantification of atrophy and the analysis of lesions in the human brain. [unreadable] [unreadable] [unreadable]